Processing facilities are often managed using industrial process control and automation systems. Many control and automation systems include multiple hierarchical layers that perform different functions. For example, lower layers could include devices that perform process control functions and model predictive control (MPC) operations, while higher layers could include devices that provide plantwide optimization solutions.
Ideally, control and plantwide optimization would be designed jointly, but one problem that arises is how to simultaneously provide decentralized controls at lower levels and centralized optimization at higher levels. Decentralized MPC solutions are often more desirable because of their operability and flexibility in dealing with process upsets, equipment failures, and maintenance. Centralized planning optimization is often more desirable because its higher-level view distills out unessential or obscuring details. However, one drawback of conventional control and automation systems lies in the lack of guaranteed solution consistency across multiple layers. In practice, plantwide planning optimization is rarely if ever implemented as part of a closed-loop control system. As a result, a significant amount of optimization benefits remains unreachable.